{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hypernets.utils import logging as hyn_logging\n",
    "\n",
    "from deeptables.models import deeptable, deepnets\n",
    "from deeptables.datasets import dsutils\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "hyn_logging.set_level(hyn_logging.WARN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = dsutils.load_bank()\n",
    "df.drop(['id'], axis=1, inplace=True)\n",
    "df_train, df_test = train_test_split(df, test_size=0.2, random_state=42)\n",
    "y = df_train.pop('y')\n",
    "y_test = df_test.pop('y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\miniconda3\\envs\\hypergbm-dev\\lib\\site-packages\\sklearn\\preprocessing\\_discretization.py:279: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  warnings.warn(\n",
      "D:\\miniconda3\\envs\\hypergbm-dev\\lib\\site-packages\\sklearn\\preprocessing\\_discretization.py:279: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  warnings.warn(\n",
      "D:\\miniconda3\\envs\\hypergbm-dev\\lib\\site-packages\\sklearn\\preprocessing\\_discretization.py:279: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  warnings.warn(\n",
      "D:\\miniconda3\\envs\\hypergbm-dev\\lib\\site-packages\\keras\\initializers\\initializers_v2.py:120: UserWarning: The initializer RandomUniform is unseeded and being called multiple times, which will return identical values  each time (even if the initializer is unseeded). Please update your code to provide a seed to the initializer, or avoid using the same initalizer instance more than once.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "22/22 [==============================] - 2s 16ms/step - loss: 947.0082 - auc: 0.5035 - val_loss: 1019.2748 - val_auc: 0.5281\n",
      "Epoch 2/20\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 867.5159 - auc: 0.5289 - val_loss: 881.8287 - val_auc: 0.5435\n",
      "Epoch 3/20\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 770.4167 - auc: 0.5493 - val_loss: 733.8837 - val_auc: 0.5382\n",
      "Epoch 4/20\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 671.2542 - auc: 0.5715 - val_loss: 705.9562 - val_auc: 0.5278\n",
      "Epoch 5/20\n",
      " 1/22 [>.............................] - ETA: 0s - loss: 380.9665 - auc: 0.5472Restoring model weights from the end of the best epoch: 2.\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 527.9287 - auc: 0.5840 - val_loss: 550.4921 - val_auc: 0.5376\n",
      "Epoch 5: early stopping\n"
     ]
    }
   ],
   "source": [
    "config = deeptable.ModelConfig(nets=deepnets.DeepFM, auto_discrete=True, metrics=['AUC'], earlystopping_patience=3)\n",
    "dt = deeptable.DeepTable(config=config)\n",
    "\n",
    "model, history = dt.fit(df_train, y, epochs=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "proba = dt.predict_proba(df_test)\n",
    "preds = dt.predict(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#model.model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': 880.5029296875, 'auc': 0.5166780352592468}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = dt.evaluate(df_test,y_test, batch_size=512, verbose=0)\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 保存模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\miniconda3\\envs\\hypergbm-dev\\lib\\site-packages\\keras\\initializers\\initializers_v2.py:120: UserWarning: The initializer RandomUniform is unseeded and being called multiple times, which will return identical values  each time (even if the initializer is unseeded). Please update your code to provide a seed to the initializer, or avoid using the same initalizer instance more than once.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'loss': 880.5029296875, 'auc': 0.5166780352592468}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tempfile\n",
    "tmpdir = tempfile.mkdtemp()\n",
    "dt.save(tmpdir)\n",
    "\n",
    "model_load = deeptable.DeepTable.load(tmpdir)\n",
    "model_load.evaluate(df_test,y_test, batch_size=512, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 输出网络架构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tensorflow.keras.utils import plot_model\n",
    "plot_model(model.model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 分析训练数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': [947.0082397460938, 867.515869140625, 770.416748046875, 671.254150390625, 527.9287109375], 'auc': [0.5034979581832886, 0.5288758873939514, 0.5493136048316956, 0.5714982151985168, 0.5840261578559875], 'val_loss': [1019.2747802734375, 881.8287353515625, 733.8837280273438, 705.9561767578125, 550.4921264648438], 'val_auc': [0.5280824303627014, 0.5435103178024292, 0.5381519794464111, 0.527760922908783, 0.5376322269439697]}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b6edd29790>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['AUC'])\n",
    "plt.plot(history.history['val_AUC'])\n",
    "plt.legend(['train', 'val'], loc='upper left') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b6eff46c40>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'],label='loss')\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.legend(['train', 'val'], loc='upper right') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
